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4 Reviews
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69 of 71 people found the following review helpful:
5.0 out of 5 stars
A well organized textbook,
By
This review is from: A Course in Probability Theory, Third Edition (Paperback)
There are several nice books in Grad-level Probability Theory. Billingsley's "Probability and Measure" is the richest one, but somehow poor organized and unpleasant printing. Resnick's "Probability Path" serve best for those who has no time to prepare first in measure theory and Lebesque integration but sacrifice some detail in latter part of the book. If you don't have previous Real Analysis training, I would suggest read Resnick first, and then find Billingsley for reference. But if you already good at measure and integration, Kai Lai Chung's "A Course in Probability Theory" still the best textbook teach step by step without losing detail. Chung's style is friendly to self studying like Resnick, but cover more detail in latter part of the book than Resnick. Chung's book is the best companion fot typical one semester course regradless what textbook your teacher choose. In the other words , Resnick helps students significantly in first half of the semester, Chung helps in the whole semester, and Billingsley may offer best effort after you took the Probability Theory course.
28 of 28 people found the following review helpful:
5.0 out of 5 stars
good graduate probability text,
By
This review is from: A Course in Probability Theory, Second Edition (Probability and Mathematical Statistics, 21) (Hardcover)
This text by Chung was one of the texts that I used when I was taking a graduate course in probability at Stanford in 1975. It is carefully written but challenging. It provides good coverage of the central limit theorem, the law of large numbers and the law of the iterated logarithm. It also covers stable laws very well. The style is one of rigorous mathematics with theorems, and lemmas given with their mathematical proofs.
The book was recently revised. The revised text does not change much but new material on measure and integration that is now commonly included in the first graduate course in probability has been added. In the 1970s at Stanford a course in measure theory was a prerequisite for the course in advanced probability although some student took it concurrently. If you plan to get this text, the revised edition is probably worth it. If you already have this edition and know your measure theory, it may not be worth it to get the new edition.
24 of 26 people found the following review helpful:
5.0 out of 5 stars
the best buy,
By A Customer
This review is from: A Course in Probability Theory, Second Edition (Probability and Mathematical Statistics, 21) (Hardcover)
"A course in probability theory", written by Kai Lai Chung, has been referred by not only mathematicians but also mathematical economists.This book is written very rigorously, but almost all of the theorems have easy-to-understand proofs. So it is not difficult to follow. Moreover, there are lots of exercises in this book. So I do recommend this book.
4 of 4 people found the following review helpful:
5.0 out of 5 stars
Probability for pure mathematicians,
By
This review is from: A Course in Probability Theory, Third Edition (Paperback)
This book assumes that you have a certain degree of mathematical maturity, but gives you very thorough proofs of the basic concepts of rigorous probability. There is no hand waving here. You are expected to have followed an introduction to measure theory. Don't expect to go through this book in a term, but when you have finished it you will be able to consider yourself to be able to come up with proofs like a mathematician. In other words it will leave you with solid foundations.
I can not imagine this book being used as an introduction. When you are finished you should be ready for a book like Foundations of Modern Probability. |
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A Course in Probability Theory, Third Edition by Kai Lai Chung (Paperback - October 23, 2000)
$92.95 $53.18
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